Machine Learning / AI Engineer

Bose Corporation; Massachusetts; Remote; USD 115,000 - 158,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Employee discount

Wellbeing perks

Job summary

Bose Corporation is seeking a Machine Learning / AI Engineer to design, train, test, and optimize ML models for consumer audio devices and edge applications. You will collaborate across ML, software, embedded systems, and hardware teams to deploy efficient AI on devices.

Ideal candidates have a strong ML/dl background, hands-on model building in Python with PyTorch or TensorFlow, and a passion for advancing on-device AI under memory and compute constraints.

Qualifications

• Bachelor’s or advanced degree in CS, EE, ML, or related field.
• 3+ years of ML/AI experience, including research or project work.
• Solid foundation in ML and deep learning with hands-on model building.
• Proficiency in Python with PyTorch or TensorFlow.
• Experience training, evaluating, and debugging models.
• Strong analytical, problem‑solving, and collaborative skills.

Responsibilities

• Build, train, and evaluate ML models for audio/embedded applications.
• Improve model accuracy while reducing latency and memory use.
• Collaborate with software, embedded, and hardware teams to deploy AI.
• Analyze results, debug issues, and guide experiments.
• Learn new ML techniques and share findings with the team.

Skills

Bachelor's degree in CS/EE/ML

3+ years ML experience

Python

PyTorch or TensorFlow

Model evaluation & debugging

Analytical problem-solving

Team collaboration

Education

Bachelor's or advanced degree in CS/EE/ML or related

Tools

PyTorch

TensorFlow

ONNX

TensorFlow Lite

Job description

At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.

Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.

Job Description

Build AI that people can hear and experience.

At Bose, we believe sound is the most powerful force on earth. As a Machine Learning / AI Engineer, you’ll help bring that belief to life - developing intelligent capabilities for the next generation of audio experiences.

If you enjoy experimenting with models, solving practical problems, and turning ideas into working technology, this is an opportunity to grow your skills while contributing to products and technology that people use every day.

About The Role

You’ll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products. You’ll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you’ll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.

What You’ll Do

• Build and experiment. Develop, train, and evaluate machine learning models for consumer audio applications.
• Make models more efficient. Explore ways to improve accuracy while reducing latency, memory use, and computational demands.
• Connect models to products. Partner with software, embedded, and hardware engineers to help bring AI capabilities onto devices.
• Investigate and improve. Analyze results, debug issues, and use testing to guide your next experiment.
• Learn and contribute. Explore emerging ML techniques, share what you discover, and bring fresh ideas to the team.

What You’ll Bring

• A bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field.
• 3+ years of relevant machine learning or AI experience, which may include applicable research or substantial project work.
• A solid foundation in machine learning and deep learning, with hands‑on experience building and evaluating models.
• Proficiency in Python and experience with a framework such as PyTorch or TensorFlow.
• Experience training, evaluating, and debugging models—and curiosity about how to make them better.
• An analytical approach to problem-solving, a willingness to ask questions, and enthusiasm for working with others.

Experience That Can Help You Stand Out

You don’t need experience in every area below. We’re interested in the strengths you bring and what you’re excited to learn.

• Techniques such as quantization, pruning, or model compression.
• Edge ML, embedded AI, or deploying models on devices with limited computing resources.
• C/C++ or deployment tools such as ONNX or TensorFlow Lite.
• Audio ML, speech processing, acoustic sensing, or related applications.
• Emerging AI technologies and AI-assisted engineering tools.

At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Remote, Massachusetts is: $115,000-$158,200.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.